Senior Data & Platform Engineer – Veterinary Technology
TruelogicAbout Truelogic
At Truelogic we are a leading provider of nearshore staff augmentation services headquartered in New York. For over two decades, we’ve been delivering top-tier technology solutions to companies of all sizes, from innovative startups to industry leaders, helping them achieve their digital transformation goals.
Our team of 600+ highly skilled tech professionals, based in Latin America, drives digital disruption by partnering with U.S. companies on their most impactful projects. Whether collaborating with Fortune 500 giants or scaling startups, we deliver results that make a difference.
By applying for this position, you’re taking the first step in joining a dynamic team that values your expertise and aspirations. We aim to align your skills with opportunities that foster exceptional career growth and success while contributing to transformative projects that shape the future.
Our Client
A leading innovator in the veterinary technology space, providing a comprehensive ecosystem of practice management software, AI tools, and clinical decision support used by professionals worldwide.
Job Summary
As a Senior Data Engineer, you will take end-to-end ownership of a rapidly scaling data platform, driving the ingestion, transformation, storage, and delivery of critical analytics for veterinary clinics. Working within a high-ownership, fully remote engineering team, you will ensure the health and reliability of complex pipelines, leverage modern infrastructure-as-code practices, and establish robust data quality standards. The ideal candidate is a battle-tested builder who has previously constructed data platforms from the ground up, seamlessly combining deep data warehousing expertise with hands-on infrastructure management.
Responsibilities
Take end-to-end ownership of the data platform's reliability, encompassing pipelines, warehousing, transformations, and observability.
Design, build, and maintain robust data pipelines using Apache Airflow, orchestrating complex workflows across batch and near-real-time workloads.
Manage and optimize the primary Snowflake data warehouse, handling schema design, clustering keys, materialized views, access controls, and strict cost governance.
Build and maintain the dbt transformation layer, including model design, incremental strategies, dependency management, and documentation.
Deploy and operate data platform services on Kubernetes (EKS), independently managing workloads, debugging pod issues, and tuning resource requests.
Provision and manage data platform infrastructure, including Snowflake resources and Airflow, utilizing Terraform.
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